Complexity of cortical wave patterns of the wake mouse cortex

• Published in: Nature communications Vol. 14; no. 1; p. 1434
• Main Authors: Liang, Yuqi, Liang, Junhao, Song, Chenchen, Liu, Mianxin, Knöpfel, Thomas, Gong, Pulin, Zhou, Changsong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15.03.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 14; 14/35; 14/56; 14/63; 631/378/116/2393; 631/378/2649/1398; 631/378/3920; Activity patterns; Anesthesia; Animals; Brain; Cerebral Cortex; Complexity; Computational neuroscience; Consciousness; Drugs; Electric potential; Humanities and Social Sciences; Mice; Mouse devices; multidisciplinary; Neuroimaging; Physics; Propagation; Science; Science (multidisciplinary); Sleep and wakefulness; Unconsciousness; Velocity; Voltage; Wakefulness
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-023-37088-6

Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolution optical voltage imaging of mice transitioning from barbiturate-induced anesthesia to wakefulness (N = 5) and awake mice (N = 4). We find that, as the brain transitions into wakefulness, there is a reduction in hemisphere-scale voltage waves, and an increase in local wave events and complexity. A neural mass model recapitulates the essential cellular-level features and shows how the dynamical competition between global and local spatiotemporal patterns and long-range connections can explain the experimental observations. These mechanisms possibly endow the awake cortex with enhanced integrative processing capabilities. The cerebral cortex has ongoing electrical activities with rich and complex patterns in space and time. Here, the authors use optical voltage imaging in mice and computational methods, relating these complexities to different levels of wakefulness.